[英]Pandas: Create new dataframe based on existing dataframe
what is the most elegant way to create a new dataframe from an existing dataframe, by 1. selecting only certain columns and 2. renaming them at the same time?通过 1. 仅选择某些列和 2. 同时重命名它们,从现有数据帧创建新数据帧的最优雅方法是什么?
For instance I have the following dataframe, where I want to pick column B, D and F and rename them into X, Y, Z例如,我有以下数据框,我想在其中选择列 B、D 和 F 并将它们重命名为 X、Y、Z
base dataframe基础数据框
A B C D E F
1 2 3 4 5 6
1 2 3 4 5 6
new dataframe新数据框
X Y Z
2 4 6
2 4 6
您可以选择和重命名一行中的列
df2=df[['B','D','F']].rename({'B':'X','D':'Y','F':'Z'}, axis=1)
Slightly more general selection of every other column:每隔一列的更一般选择:
df = pd.DataFrame({'A':[1,2,3], 'B':[4,5,6],
'C':[7,8,9], 'D':[10,11,12]})
df_half = df.iloc[:, ::2]
with df_half
being: df_half
是:
A C
0 1 7
1 2 8
2 3 9
You can then use the rename method mentioned in the answer by @G.然后,您可以使用@G 的答案中提到的重命名方法。 Anderson or directly assign to the columns: Anderson 或直接分配给列:
df_half.columns = ['X','Y']
returning:返回:
X Y
0 1 7
1 2 8
2 3 9
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